Molecular weight distribution worked examples

Much has been written on RAFT polymerization under emulsion and miniemulsion conditions. Most work has focused on S polymerization,409-520 521 although polymerizations of BA,461 522 methacrylates382-409 and VAc471-472 have also been reported. The first communication on RAFT polymerization briefly mentioned the successful semi-batch emulsion polymerization of BMA with cumyl dithiobenzoate (175) to provide a polymer with a narrow molecular weight distribution.382 Additional examples and discussion of some of the important factors for successful use of RAFT polymerization in emulsion and miniemulsion were provided in a subsequent paper.409 Much research has shown that the success in RAFT emulsion polymerization depends strongly on the choice of RAFT agent and polymerization conditions.214-409-520027... 

This work describes the design, operation and application of the continuous GPC viscosity detector for the characterization of the molecular weight distribution of polymers. Details of the design and factors affecting the precision and accuracy of results are discussed along with selected examples of polymers with narrow and broad molecular weight distribution. 

The pioneering work dealing with the molecular weight and molecular weight distribution of polymer produced in emulsion polymerization can be found in the literature [106,107]. For example, the following expressions can be used to calculate the molecular weight and molecular weight distribution of polymer obtained from the Smith-Ewart Interval II in emulsion polymerization [106]. 

Finally, we note that the use of a discrete spectrum involves the use of an empirical equation to fit data. The resulting constants have no physical significance, and the resulting function will have local features that are artifacts of the model and do not reflect the structure of the polymer. This can cause trouble, for example if this function is used to infer the molecular weight distribution. For such a purpose, it may thus be preferable to work with a continuous spectrum function such as H(t) or L(t). Honerkamp and Weese [42] reported a nonlinear regression with regularization technique (NLRG) that takes into account noise in the data and yields a smooth relaxation spectrum. 

For example, a powerful regularization technique can be used to invert the single integral of the model. Or a form for the molecular weight distribution can be assumed. Such models work well when the polydispersity is modest (PI < 4) and when there is very little material present for which M is near or below M. ... 

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